The client is a company that has a rapidly growing Real Estate product in its portfolio. This product brings together transaction participants and allows them to quickly and easily access transaction details, engage with other parties and share the documents required for proper transaction completion.
The client faced the need to automate multi-environment continuous integration and deployment process of microservices, move the front-end part to CDN as well as deploy multi-environment infrastructure as a code.
1. Amazon Route 53 provides DNS configuration.
2. AWS WAF is a web application firewall that protects the Real Estate platform against common web exploits.
3. Amazon CloudFront is a fast content delivery network (CDN) that speeds up distribution of static and dynamic web content.
4. Elastic Load Balancing (Application Load Balancer) distributes across the AWS Auto Scaling group of the Real Estate platform instances (Amazon ECS Cluster) in multiple Availability Zones.
5. On Amazon ECS Cluster, there is a dockerized application that consists of the Real Estate platform code itself, Nginx webserver and PHP, etc.
6. Amazon Elasticsearch Service manages Elastic Search Service for Real Estate platform catalog search.
7. Amazon ElastiCache for Redis provides a caching layer for the database.
8. The use of Amazon Aurora or Amazon RDS allows to simplify database administration (including high availability and multi-master configuration).
The solution also features a CI/CD environment that uses GitLab CI to automate deployment and release processes. CI/CD consists of two independent pipelines for the front-end and back-end parts. All secrets for the deployment process are stored securely in GitLab CI. All infrastructure is deployed via Terraform. It’s also used to deploy back-end microservices with GitLab pipelines. State files for Terraform are stored in AWS S3 so they can be easily accessible from local and CI environments.
For the front-end part, a CDN service was configured using AWS CloudFront. The front-end pipeline deploys changes to S3 and then updates content on CloudFront. Both pipelines are triggered automatically and deploy changes to different environments.
Terraform, AWS, GitLab CI, Amazon ECS, Amazon ElastiCache, Amazon CloudFront, Amazon CloudWatch, Amazon RDS, Amazon EFS, Amazon Route 53, AWS WAF, Elastic Load Balancing.
With the delivered solution, the client has got a highly available and resilient to failures microservice architecture powered by AWS ECS with CloudFront and a fully managed and automated deployment process powered by GitLab CI.
The client experienced the need to automate the deployment process of microservices and simplify the release process. One of the requirements was to migrate Docker containers to AWS ECS and move existing infrastructure to Terraform.
The client had a manual multi-environment infrastructure deployment аnd no continuous integration & continuous deployment automation. That significantly impacted the speed of product development, release, and delivery cadence of new application versions in general. Besides, it required a considerable part of the development team capacity to process it manually.
The client had high costs for development, deployment, and, most importantly, operation of the data platform including Data Lake, Ingestion, and ML Pipelines. The pipelines were mostly running in EC2 instances, which led to the increased cost of operations and required a significant amount of time to deploy and test the pipelines in lower environments.
The client came with a request to automate and unify the deployment process of serverless applications on AWS Lambda. Having manual deployments before, the customer was facing inconveniences and difficulties, including non-uniform environment setup (versions of Serverless, Python, Node, and so on were inconsistent) and inability to control the environment changes in one place.
The client needed to strengthen collaboration within the data scientists team by moving research capabilities into cloud workloads. Besides, they wanted to automate and unify the deployment process of AWS resources. That, in turn, would decrease the time and effort required for a team of data scientists to build and test their models.
CI/CD (Continuous Integration/Continuous Deployment) offers a seamless bridge from development to deployment. Further, in the evolving world of mobile app development, efficiency and adaptability are key.
At Matoffo, we specialize in customizing CI/CD solutions that cater to cross-platform mobile application development. We focus on improving the technical workflow and enhancing our client’s overall business performance and user experience.
Our primary goal is value delivery for the client by resolving technical challenges and assisting them to achieve their objectives. AWS cloud solutions are great toolset which we use to make it happens, primary by outstanding agility, where companies could scale up cloud resources as needed and significantly decrease time from idea to market as well as seamless adopt rapidly growing tech capabilities to transform their businesses to be competitive in the market.
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